@inproceedings{potapczyk-przybysz-2020-srpols,
    title = "{SRPOL}`s System for the {IWSLT} 2020 End-to-End Speech Translation Task",
    author = "Potapczyk, Tomasz  and
      Przybysz, Pawel",
    editor = {Federico, Marcello  and
      Waibel, Alex  and
      Knight, Kevin  and
      Nakamura, Satoshi  and
      Ney, Hermann  and
      Niehues, Jan  and
      St{\"u}ker, Sebastian  and
      Wu, Dekai  and
      Mariani, Joseph  and
      Yvon, Francois},
    booktitle = "Proceedings of the 17th International Conference on Spoken Language Translation",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.iwslt-1.9/",
    doi = "10.18653/v1/2020.iwslt-1.9",
    pages = "89--94",
    abstract = "We took part in the offline End-to-End English to German TED lectures translation task. We based our solution on our last year`s submission. We used a slightly altered Transformer architecture with ResNet-like convolutional layer preparing the audio input to Transformer encoder. To improve the model`s quality of translation we introduced two regularization techniques and trained on machine translated Librispeech corpus in addition to iwslt-corpus, TEDLIUM2 andMust{\_}C corpora. Our best model scored almost 3 BLEU higher than last year`s model. To segment 2020 test set we used exactly the same procedure as last year."
}